ITR: Foundations of Visual Search

项目摘要：本研究旨在开发灵活的、通用的视觉搜索系统，能够在真实的、混乱的环境中搜索对象。这项研究将包括对人类和灵长类动物进行广泛的心理物理和生理实验，以模拟这种行为的人工系统原型。该研究的目标可以方便地分为四个目标：目标1：开发和原型一个革命性的相机凝视控制设备被称为远程高速主动视觉环境，或RHAVEN。RHAVEN将允许远程控制远程摄像机的视线，使用眼球运动，就像直接观看场景一样迅速和自然。目标2：开发视觉搜索的最佳统计边界，通过将其作为贝叶斯问题，产生最大后验（MAP）解决方案，首先，使用最少的注视在视觉场景中找到目标，其次，在给定当前注视的情况下选择下一个注视。目标3：构建基于注视点自然场景统计的视觉搜索模型。视觉上重要的图像结构可以通过分析由眼球运动和注视采样的自然场景的统计来推断。目标4：在视觉搜索任务中对清醒、行为的灵长类动物进行神经生理学研究。测量并分析清醒、行为正常的猴子的搜索表现，同时测量大脑额叶眼区（FEF）神经群的反应，这有助于控制眼球跳动。更广泛的影响：这项研究的结果将显著影响许多国家优先事项：搜索大型视觉数据库，机器人导航，安全成像，生物医学搜索，视觉神经科学等。从视觉搜索的基本理论中获益的场景是很容易想象的。例如：在机场保安系统中搜寻嫌疑犯的面孔；检查互联网流中的可疑材料；乳房x光检查中病灶的半自动搜索；在恶劣环境中驾驶机器人车辆绕过障碍物；导航巨大的可视化数据库等。

Project AbstractThis study is directed towards developing flexible, general-purpose Visual Search systems capable of Searching for objects in real, cluttered environments. The research will include extensive psychophysical and physiological experiments on humans and primates that will prototype artificial systems that mimic this behavior. The goals of the study can be conveniently divided into four Aims:Aim 1: Develop and prototype a revolutionary camera gaze control device dubbed Remote High-Speed Active Visual Environment, or RHAVEN. RHAVEN will allow telepresent control of the gaze of a remote camera using eye movements as rapidly and naturally as if viewing the scene directly.Aim 2: Develop optimal statistical bounds on Visual Search, by casting it as a Bayesian problem, yielding a maximum a posteriori (MAP) solutions for firstly, finding a target in a visual scene using a smallest number of fixations, and secondly, for next-fixation selection given a current fixation.Aim 3: Construct models for Visual Search based on Natural Scene Statistics at the point of gaze. Visually important image structures can be inferred by analyzing the statistics of natural scenes sampled by eye movements and fixations.Aim 4: Conduct neurophysiological studies on awake, behaving primates during Visual Search tasks. Measure and analyze search performance in awake, behaving monkeys, while measuring the responses of neural populations in the brain's frontal eye fields (FEF) which help control saccadic eye movements.Broader Impact: The results of this research should significantly impact numerous National Priorities: Searching Large Visual Databases, Robotic Navigation, Security Imaging, Biomedical Search, Visual Neuroscience, and many others. It is easy to envision scenarios that would benefit by a fundamental theory of Visual Search. For example: searching for suspect faces in airport security systems; examining internet streams for questionable material; semi-automatic search for lesions in mammograms; steering robotic vehicles around obstacles in hostile environs; navigating huge visual data libraries, etc.